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ENN (patch level)

Source: R/lsm_p_enn.R
lsm_p_enn.Rd

Euclidean Nearest-Neighbor Distance (Aggregation metric)

Usage

lsm_p_enn(landscape, directions = 8, verbose = TRUE)

Arguments

landscape

A categorical raster object: SpatRaster; Raster* Layer, Stack, Brick; stars or a list of SpatRasters.

directions

The number of directions in which patches should be connected: 4 (rook's case) or 8 (queen's case).

verbose

Print warning message if not sufficient patches are present

Value

tibble

Details

$$ENN = h_{ij}$$ where \(h_{ij}\) is the distance to the nearest neighbouring patch of the same class i in meters

ENN is an 'Aggregation metric'. The distance to the nearest neighbouring patch of the same class i. The distance is measured from edge-to-edge. The range is limited by the cell resolution on the lower limit and the landscape extent on the upper limit. The metric is a simple way to describe patch isolation.

Units

Meters

Range

ENN > 0

Behaviour

Approaches ENN = 0 as the distance to the nearest neighbour decreases, i.e. patches of the same class i are more aggregated. Increases, without limit, as the distance between neighbouring patches of the same class i increases, i.e. patches are more isolated.

References

McGarigal K., SA Cushman, and E Ene. 2023. FRAGSTATS v4: Spatial Pattern Analysis Program for Categorical Maps. Computer software program produced by the authors; available at the following web site: https://www.fragstats.org

McGarigal, K., and McComb, W. C. (1995). Relationships between landscape structure and breeding birds in the Oregon Coast Range. Ecological monographs, 65(3), 235-260.

See also

lsm_c_enn_mn, lsm_c_enn_sd, lsm_c_enn_cv,
lsm_l_enn_mn, lsm_l_enn_sd, lsm_l_enn_cv

Examples

landscape <- terra::rast(landscapemetrics::landscape)
lsm_p_enn(landscape)
#> # A tibble: 28 × 6
#>    layer level class    id metric value
#>    <int> <chr> <int> <int> <chr>  <dbl>
#>  1     1 patch     1     1 enn     7   
#>  2     1 patch     1     2 enn     4   
#>  3     1 patch     1     3 enn     2   
#>  4     1 patch     1     4 enn     6.32
#>  5     1 patch     1     5 enn     5   
#>  6     1 patch     1     6 enn     2.24
#>  7     1 patch     1     7 enn     2   
#>  8     1 patch     1     8 enn     4.12
#>  9     1 patch     1     9 enn     4.12
#> 10     1 patch     2    10 enn     4.47
#> # ℹ 18 more rows